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<div class="title">Fp16SupportTest.cpp</div> </div>
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<a href="_fp16_support_test_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_descriptors_8hpp.html">armnn/Descriptors.hpp</a>&gt;</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_runtime_8hpp.html">armnn/IRuntime.hpp</a>&gt;</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_network_8hpp.html">armnn/INetwork.hpp</a>&gt;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_half_8hpp.html">Half.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_graph_8hpp.html">Graph.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_optimizer_8hpp.html">Optimizer.hpp</a>&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_cpu_tensor_handle_8hpp.html">backendsCommon/CpuTensorHandle.hpp</a>&gt;</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="preprocessor">#include &lt;boost/core/ignore_unused.hpp&gt;</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="preprocessor">#include &lt;boost/test/unit_test.hpp&gt;</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="preprocessor">#include &lt;set&gt;</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<a class="code" href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(Fp16Support)</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;</div><div class="line"><a name="l00024"></a><span class="lineno"><a class="line" href="_fp16_support_test_8cpp.html#a6aab4e0ffa70a022cce19a8e50fca1b5"> 24</a></span>&#160;<a class="code" href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(Fp16DataTypeSupport)</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;{</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> inputLayer1 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(1, <span class="stringliteral">&quot;input1&quot;</span>);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> inputLayer2 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(2, <span class="stringliteral">&quot;input2&quot;</span>);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> additionLayer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_addition_layer.html">AdditionLayer</a>&gt;(<span class="stringliteral">&quot;addition&quot;</span>);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> outputLayer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> fp16TensorInfo({1, 2, 3, 5}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; inputLayer1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(additionLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; inputLayer2-&gt;GetOutputSlot(0).Connect(additionLayer-&gt;GetInputSlot(1));</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; additionLayer-&gt;GetOutputSlot(0).Connect(outputLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; inputLayer1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(fp16TensorInfo);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; inputLayer2-&gt;GetOutputSlot().SetTensorInfo(fp16TensorInfo);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; additionLayer-&gt;GetOutputSlot().SetTensorInfo(fp16TensorInfo);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(inputLayer1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(inputLayer2-&gt;GetOutputSlot(0).GetTensorInfo().GetDataType() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(additionLayer-&gt;GetOutputSlot(0).GetTensorInfo().GetDataType() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;}</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;</div><div class="line"><a name="l00048"></a><span class="lineno"><a class="line" href="_fp16_support_test_8cpp.html#a9cd77c53f585802ea8f9c1afedb641bf"> 48</a></span>&#160;<a class="code" href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(Fp16AdditionTest)</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;{</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="keyword">using namespace </span>half_float::literal;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="comment">// Create runtime in which test will run</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options));</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">INetwork::Create</a>());</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* inputLayer1 = net-&gt;AddInputLayer(0);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* inputLayer2 = net-&gt;AddInputLayer(1);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* additionLayer = net-&gt;AddAdditionLayer();</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* outputLayer = net-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; inputLayer2-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="comment">//change to float16</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> fp16TensorInfo(<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>({4}), <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(fp16TensorInfo);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; inputLayer2-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(fp16TensorInfo);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(fp16TensorInfo);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="comment">// optimize the network</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; std::vector&lt;BackendId&gt; backends = {<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>};</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime-&gt;GetDeviceSpec());</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="comment">// Loads it into the runtime.</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <a class="code" href="namespacearmnn.html#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; runtime-&gt;LoadNetwork(netId, std::move(optNet));</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; std::vector&lt;Half&gt; input1Data</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; 1.0_h, 2.0_h, 3.0_h, 4.0_h</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; };</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; std::vector&lt;Half&gt; input2Data</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; {</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; 100.0_h, 200.0_h, 300.0_h, 400.0_h</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; };</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <a class="code" href="namespacearmnn.html#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; {0,<a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a>(runtime-&gt;GetInputTensorInfo(netId, 0), input1Data.data())},</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; {1,<a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a>(runtime-&gt;GetInputTensorInfo(netId, 0), input2Data.data())}</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; };</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; std::vector&lt;Half&gt; outputData(input1Data.size());</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <a class="code" href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; {0,<a class="code" href="classarmnn_1_1_tensor.html">Tensor</a>(runtime-&gt;GetOutputTensorInfo(netId, 0), outputData.data())}</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; };</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="comment">// Does the inference.</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; runtime-&gt;EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <span class="comment">// Checks the results.</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; BOOST_TEST(outputData == std::vector&lt;Half&gt;({ 101.0_h, 202.0_h, 303.0_h, 404.0_h})); <span class="comment">// Add</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;}</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160;<a class="code" href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.html#l00013">InputLayer.hpp:13</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_html_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot &amp; GetInputSlot(unsigned int index) const =0</div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div>
<div class="ttc" id="_optimizer_8hpp_html"><div class="ttname"><a href="_optimizer_8hpp.html">Optimizer.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_html_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector&lt; std::pair&lt; LayerBindingId, class Tensor &gt; &gt; OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00226">Tensor.hpp:226</a></div></div>
<div class="ttc" id="namespacearmnn_html_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &amp;network, const std::vector&lt; BackendId &gt; &amp;backendPreferences, const IDeviceSpec &amp;deviceSpec, const OptimizerOptions &amp;options=OptimizerOptions(), Optional&lt; std::vector&lt; std::string &gt; &amp;&gt; messages=EmptyOptional())</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l00807">Network.cpp:807</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="namespacearmnn_html_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">armnn::BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.html#l00170">ConstTensorLayerVisitor.cpp:170</a></div></div>
<div class="ttc" id="_i_runtime_8hpp_html"><div class="ttname"><a href="_i_runtime_8hpp.html">IRuntime.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00397">Graph.hpp:397</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &amp;destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_html_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &amp;tensorInfo)=0</div></div>
<div class="ttc" id="classarmnn_1_1_tensor_html"><div class="ttname"><a href="classarmnn_1_1_tensor.html">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00191">Tensor.hpp:191</a></div></div>
<div class="ttc" id="namespacearmnn_html_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.html#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector&lt; std::pair&lt; LayerBindingId, class ConstTensor &gt; &gt; InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00225">Tensor.hpp:225</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00058">Layer.cpp:58</a></div></div>
<div class="ttc" id="_descriptors_8hpp_html"><div class="ttname"><a href="_descriptors_8hpp.html">Descriptors.hpp</a></div></div>
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<div class="ttc" id="_file_only_profiling_decorator_tests_8cpp_html_a0c262ba6f6c189a2d092d127c1b7627b"><div class="ttname"><a href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a></div><div class="ttdeci">BOOST_CHECK(profilingService.GetCurrentState()==ProfilingState::WaitingForAck)</div></div>
<div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.html#l00013">OutputLayer.hpp:13</a></div></div>
<div class="ttc" id="namespacearmnn_html_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div>
<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
<div class="ttc" id="namespacearmnn_html_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr&lt; INetwork, void(*)(INetwork *network)&gt; INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00085">INetwork.hpp:85</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_runtime_html_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &amp;options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.html#l00032">Runtime.cpp:32</a></div></div>
<div class="ttc" id="_profiler_tests_8cpp_html_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div>
<div class="ttc" id="_cpu_tensor_handle_8hpp_html"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.html">CpuTensorHandle.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_addition_layer_html"><div class="ttname"><a href="classarmnn_1_1_addition_layer.html">armnn::AdditionLayer</a></div><div class="ttdoc">This layer represents an addition operation. </div><div class="ttdef"><b>Definition:</b> <a href="_addition_layer_8hpp_source.html#l00013">AdditionLayer.hpp:13</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_html"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00061">INetwork.hpp:61</a></div></div>
<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00095">Tensor.hpp:95</a></div></div>
<div class="ttc" id="_output_shape_of_squeeze_8cpp_html_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
<div class="ttc" id="namespacearmnn_html_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr&lt; IOptimizedNetwork, void(*)(IOptimizedNetwork *network)&gt; IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00544">INetwork.hpp:544</a></div></div>
<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_html"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00041">IRuntime.hpp:41</a></div></div>
<div class="ttc" id="_graph_8hpp_html"><div class="ttname"><a href="_graph_8hpp.html">Graph.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_html_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &amp;destination)=0</div></div>
<div class="ttc" id="_file_only_profiling_decorator_tests_8cpp_html_a6560146509197f3e197d8d36f76c1347"><div class="ttname"><a href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a></div><div class="ttdeci">armnn::Runtime::CreationOptions::ExternalProfilingOptions options</div><div class="ttdef"><b>Definition:</b> <a href="_file_only_profiling_decorator_tests_8cpp_source.html#l00045">FileOnlyProfilingDecoratorTests.cpp:45</a></div></div>
<div class="ttc" id="namespacearmnn_html_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.html#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00019">IRuntime.hpp:19</a></div></div>
<div class="ttc" id="namespacearmnn_html_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr&lt; IRuntime, void(*)(IRuntime *runtime)&gt; IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00024">IRuntime.hpp:24</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00063">Layer.cpp:63</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_html_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot &amp; GetOutputSlot(unsigned int index) const =0</div></div>
<div class="ttc" id="_i_network_8hpp_html"><div class="ttname"><a href="_i_network_8hpp.html">INetwork.hpp</a></div></div>
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